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Record W1518920624 · doi:10.5539/mas.v9n6p236

Determination of Measurements of the Female Population of the Republic of Kazakhstan

2015· article· en· W1518920624 on OpenAlexvenueno aff
Tavarkul Aljanovna Baskimbayeva, Yerkin Dhumahanovich Danebergenov

Bibliographic record

VenueModern Applied Science · 2015
Typearticle
Languageen
FieldMedicine
TopicTechnology and Human Factors in Education and Health
Canadian institutionsnot available
Fundersnot available
KeywordsTypologyAnthropometryStatisticsPopulationDemographyRegression analysisClothingMathematicsRegressionLinear regressionGeographySociology

Abstract

fetched live from OpenAlex

Article deals with the problem of the size typology development of the female population of the Republic of Kazakhstan. Based on the statistical data of anthropometric measurements of the female population the absolute values of the basic dimensional characteristics for four age groups are determined. Based on the correlative-regression analysis the dependences of subordinate measurements from the leading were revealed. The analysis of the numerical values of the measurements of the female population depending on the age factor is given. On the basis of the calculation of the regression equations, the values of dimensional attributes of subordinates for typical figures used in the design of clothing are determined. On the example of the typical figure 164-96-104 the results of calculations of the absolute values of subordinate measurable traits for women of all age groups in comparison with the total age group and data of the previous dimensional typology are given.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.120
GPT teacher head0.354
Teacher spread0.234 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2015
Admission routes1
Has abstractyes

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